Dawidowicz Jacek
Faculty of Civil and Environmental Engineering, Bialystok University of Technology, ul. Wiejska 45A, Białystok, Poland.
Neural Comput Appl. 2018;30(8):2531-2538. doi: 10.1007/s00521-017-2844-8. Epub 2017 Jan 12.
Water distribution system design is inherently associated with hydraulic calculations that require thorough evaluation of obtained results and accuracy of the applied solution. Currently, there are no programs that will replace a designer in these tasks, and there likely will not be such programs. However, some individuals are trying to develop computer programs featuring a certain degree of creativity to facilitate user decision making. In water distribution system design and hydraulic calculations, one should, inter alia, check pressure heads in different parts of the system. It is also important to establish whether the system should contain one or more pressure zones. This determination is connected with the appropriate location of booster and pressure reducing stations. In this paper, the nominal variable is defined. The classes of this variable describe problems related to a value of pressure and division of the water distribution system into pressure zones. By choosing one of the classes, an artificial neural network determines the problems that may arise in a given part of the water distribution system. The classification is conducted based on neural network input variables describing the specific parameters that affect water distribution system design, such as land relief, loss of pressure, pipe roughness and distance to a water supply. The paper presents a new approach that extends traditional methods of hydraulic calculations for water distribution systems by introducing the evaluation of a pressure head and the analysis of design concepts of pressure zones by using artificial neural networks.
配水系统设计本质上与水力计算相关，而水力计算需要对所得结果进行全面评估，并确保所应用解决方案的准确性。目前，尚无程序能够在这些任务中取代设计师，而且可能也不会有这样的程序。然而，一些人正在尝试开发具有一定创造性的计算机程序，以方便用户进行决策。在配水系统设计和水力计算中，尤其应当检查系统不同部位的压头。确定系统应包含一个还是多个压力区也很重要。这一确定与增压站和减压站的适当位置有关。本文定义了名义变量。该变量的类别描述了与压力值以及将配水系统划分为压力区相关的问题。通过选择其中一个类别，人工神经网络可确定在配水系统给定部位可能出现的问题。分类是基于描述影响配水系统设计的特定参数的神经网络输入变量进行的，这些参数如地形起伏、压力损失、管道粗糙度以及到水源的距离等。本文提出了一种新方法，通过引入压头评估以及利用人工神经网络分析压力区的设计概念，扩展了配水系统传统的水力计算方法。
